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In linguistics, lexical similarity is a measure of the degree to which the word sets of two given languages are similar. A lexical similarity of 1 (or 100%) would mean a total overlap between vocabularies, whereas 0 means there are no common words. There are different ways to define the lexical similarity and the results vary accordingly.
Eclipse (compare) Ediff: ExamDiff Pro: No Yes Yes Yes Yes Far Manager (compare) Yes No Yes No Yes fc: No Optional FileMerge (aka opendiff) No No No Optional Guiffy SureMerge: filesystem dependent Yes Yes IntelliJ IDEA (compare) jEdit JDiff plugin: Lazarus Diff Meld: Notepad++ (compare) No No No Yes Perforce P4Merge — No No No Yes Pretty Diff ...
BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU.
SimRank is a general similarity measure, based on a simple and intuitive graph-theoretic model.SimRank is applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects.
Software suite to search and cluster huge sequence sets. Similar sensitivity to BLAST and PSI-BLAST but orders of magnitude faster: Protein: Steinegger M, Mirdita M, Galiez C, Söding J [10] 2017 USEARCH Ultra-fast sequence analysis tool: Both: Edgar, R. C. (2010). "Search and clustering orders of magnitude faster than BLAST". Bioinformatics.
2. Sentence: S 3. Verb phrase: VP 4. Clause: C 5. T-unit: T 6. Dependent clause: DC 7. Complex T-unit CT 8. Coordinate phrase CP 9. Complex nominal CN 10. Syntactic complexity indices Length of production units Mean length of sentence MLS 11. Mean length of T-unit MLT 12. Mean length of clause MLC 13. Overall sentence complexity Clause per ...
Calculate a similarity score that is the sum of the joined regions penalising for each gap 20 points. This initial similarity score ( initn ) is used to rank the library sequences. The score of the single best initial region found in step 2 is reported ( init1 ).
The higher the Jaro–Winkler distance for two strings is, the less similar the strings are. The score is normalized such that 0 means an exact match and 1 means there is no similarity. The original paper actually defined the metric in terms of similarity, so the distance is defined as the inversion of that value (distance = 1 − similarity).